Technical Field
The invention relates to a method for the planning of trips in the transport of persons, based on a preferably statistical forecasting model, particularly for the purpose of capacity planning, for the purpose of optimizing the deployment of vehicle fleets, for the purpose of planning test runs, etc., preferably in the regional transit of persons, wherein the forecasting model takes into account the behavior of passengers over a profile of days, weeks, and/or years, via parameters.
This is basically a planning method for the purpose of controlling vehicle fleets in the regional transit of persons, wherein the method can also be used for planning test runs, by way of example. It does not matter whether the passenger transit takes places by road or by rail. In principle, the method can be used in the planning of any manner of passenger transit.
Description of Related Art
In practice, the classical approach is known wherein the number of passengers is detected, and the degree of usage—of what is most commonly public regional passenger transit—is determined in correlation with the line, the time, the day of the week, and the type of day—weekday, holiday, etc. The detection of entering and exiting passengers is carried out in automatic passenger counting via sensors in the vehicle doors, which continuously determine the degree of usage of each vehicle. For cost reasons, the amount of technology which must be deployed for this purpose is only used in a few vehicles of the vehicle fleet, by many transit operators, such that it is necessary to use the accordingly equipped counting vehicles specifically on the lines/circuits which are suitable to serve as the basis of calculations of required capacity using statistical models. The determination of routes which will be operated—also called test run planning—is very important for precisely specifying samples, particularly for the purpose of establishing a basis for a forecasting model for extrapolating a route network. The samples take into account the layering of process parameters, different types of times of day (holidays, weekdays, weekends), lines, and also sample sizes.
In current practice, a wide variety of forecasting models are known. The Association of German Transport Companies (VDV) presents, in the VDV Magazine No. 457, printed November 2006, under “Rahmenlastenheft [Framework Specifications Sheet]” automatic passenger counting systems, statistical foundations, notes, and recommendations. Information on passenger counting systems in rail transport is known from the Magazine No. 458, printed on November 2008. The recommendations of VDV are based on the considerations given above.
The forecasting models implemented to date approximate the actual conditions according to underlying basic parameters. Even though essential parameters are in fact taken into account, the quality of the forecasts is subject to enormous variations in the passenger occupancy, and particularly over the entire year. In particular, variability occurs when the weather affects the behavior of passengers. The statistical models are significantly skewed as a result. As a result, the number of planning parameters used to date is not adequate for representative samples. When the recommendations issued by the VDV are followed as closely as possible, the forecasts deviate from the real situation, at the latest, when unforeseeable weather changes have a drastic effect on the behavior of passengers.